The Encoder in a Transformer architecture is like a translator that converts input text into a numerical representation that the model can understand. It processes the input text, capturing relationships and dependencies between words using self-attention mechanisms. This creates a rich, contextualized representation of the input that the Decoder can then use for various language tasks.
In simpler terms: The Encoder is like a language expert who reads a text and breaks it down into its core meaning and structure, making it easier for the Decoder to generate relevant and accurate output.
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